Enterprise storage systems currently available are proprietary storage appliances that integrate the storage controller functions and the storage media into the same physical unit. This centralized model makes it harder to independently scale the storage systems' capacity, performance and cost. Users can get tied to one expensive appliance without the flexibility of adapting it to different application requirements that may change over time. For small and medium scale enterprise, this may require huge upfront capital cost. For larger enterprise datacenters, new storage appliances are added as the storage capacity and performance requirements increase. These operate in silos and impose significant management overheads.
Due to non-deterministic and non-uniform nature of workloads running on a the enterprise storage system, each storage node of a multi-node system has a potential of being imbalanced in storage capacity or input/output (I/O) servicing capacity in comparison to other nodes in the cluster. This could result in some storage nodes becoming full before others and thereby leading to uneven usage of storage. Alternatively, some compute nodes could bear the I/O load more than other nodes.